Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add danielkinneyspears/federal-proposal-skills --skill responding-to-rfisgit clone --depth 1 https://github.com/danielkinneyspears/federal-proposal-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/danielkinneyspears/federal-proposal-skills/responding-to-rfis)<a href="https://agentmods.dev/skills/danielkinneyspears/federal-proposal-skills/responding-to-rfis"><img src="https://agentmods.dev/badge/skills/danielkinneyspears/federal-proposal-skills/responding-to-rfis/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/danielkinneyspears/federal-proposal-skills/responding-to-rfis"><img src="https://agentmods.dev/badge/skills/danielkinneyspears/federal-proposal-skills/responding-to-rfis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00097 | $0.01510 |
| Opus 5 | $0.00048 | $0.00755 |
| Sonnet 5 | $0.00019 | $0.00302 |
| Haiku 4.5 | $0.00010 | $0.00151 |
Grade A, and why
responding-to-rfis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 131 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Responding to RFIs
Draft the pre-RFP shaping responses — sources-sought responses, RFI responses, draft-RFP comments, capability statements, white papers. This is real capture work, not paperwork. A sources-sought response can influence whether an acquisition is set aside; a draft-RFP comment can change Section L or Section M; a white paper can teach the customer what to ask for. The package's capture skills name these vehicles — this skill actually writes them.
When to use this skill
Use this skill during the capture phase, whenever the government issues a pre-RFP instrument that invites an industry response: a sources-sought notice, a request for information, an industry-day request for input, or a draft RFP released for comment. Also use it to produce capability statements and white papers offered to the customer as shaping vehicles.
It does not respond to the actual RFP — that is the proposal-development skills. This skill operates before the RFP exists.
Inputs
Required: the government instrument being responded to — the sources-sought notice, RFI, draft RFP, or industry-day announcement — and its response instructions (what the government asks for, the format, the deadline).
Preferred upstream artifacts:
02-capture-plan.md: the customer knowledge, hot buttons, and shaping objectives the response should advance.00-opportunity-profile.md: the opportunity facts.05-win-strategy.md,03-competitive-assessment.md— where they exist, to align the response with the emerging win approach.
Read ../../shared/glossary.md and ../../shared/pursuit-workspace.md if not
already read this session. The procurement-integrity limits in
references/shaping-response-types.md govern this skill — read them before
drafting anything.
Intake
Ask these as a numbered list. Skip what the instrument answers.
- The instrument. What is it — a sources-sought notice, an RFI, a draft RFP, an industry-day request, or an offered white paper/capability statement? What exactly does the government ask for, in what format, by when?
- The shaping objective. What does the team want this response to achieve —
demonstrate capability, influence the set-aside decision, shape the scope,
shape Section L or M, build customer awareness? (From
02-capture-plan.mdif available.) - Capability facts. What true capability, past performance, and qualifications can the response draw on?
- The set-aside angle. For a sources-sought notice: is the team a small business or in a socioeconomic category, and does the response need to support a set-aside the team would benefit from?
- Draft-RFP specifics. For a draft RFP: which parts (scope, Section L, Section M) does the team want to comment on, and what change does it want?
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 131 lines · 97 tokens per session scan A 1242ff93fdf6
responding-to-rfis is a skill published in the GitHub repository danielkinneyspears/federal-proposal-skills (5 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 97 tokens to every session and 1,510 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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